All Campus Champions Community Call Presentation
Neocortex: An Innovative Resource for Accelerating AI and HPC Development for Rapidly Evolving Research
Access and AI research begins on the new PSC Neocortex system, an advanced AI computing system for science and engineering that leverages Cerebras Systems’ revolutionary Wafer Scale Engine
Presented on Tuesday, March 21, 2023, 3:00 – 4:00 pm (ET), by Paola Buitrago, Director of Artificial Intelligence and Big Data at the Pittsburgh Supercomputing Center (PSC), and Mei-Yu Wang (PSC).
This presentation gives an overview of Neocortex, a deployed NSF-funded AI supercomputer at PSC. Neocortex targets the acceleration of AI-powered scientific discovery by vastly shortening the time required for deep learning training and fostering greater integration of deep learning with scientific workflows. Our team recently demonstrated its capability to achieve ground-breaking results for high-performance computing applications such as computational fluid dynamics.
Neocortex democratizes access to game-changing computing power otherwise only available to tech giants for researchers. It inspires the research community to scale their AI-based research and integrate AI advances into their research workflows. Neocortex was deployed at the PSC in early 2021 and currently supports research in drug discovery, genomics, molecular dynamics, climate research, computational fluid dynamics, and many more.
The Neocortex Call for Proposals (CFP) provides opportunities to access the remarkable integrated technologies of the Cerebras CS-2 and the HPE Superdome Flex Servers available in PSC’s Neocortex system. The Spring 2023 CFP open period is from March 15 to April 12, 2023. The User access is expected to begin in mid-May 2023. For more information about Neocortex Spring 2023 CFP, please visit the CFP web page.
For more information about Neocortex, explore the Neocortex project page. For questions about this webinar, please email neocortex@psc.edu.
This material is based upon work supported by the National Science Foundation under Grant Number 2005597. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.